Optimal short-term scheduling for a large-scale cascaded hydro system

Piekutowski, M.; Frowd, Roderick J.

doi:10.1109/pica.1993.291004

Cited by 45 publications

(56 citation statements)

References 2 publications

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“…Numerical efficiency in equation (9) η is estimated by interpolating in the corresponding turbine efficiency hill curves the unit speed and unit flow values, calculated in turn by substituting u j and h in (4) and (5). The generation characteristic of a hydro plant with four generating units is plotted in Fig.…”

Section: Plant Generation Characteristicmentioning

confidence: 99%

“…In linear programming based models, the hydro generation characteristic is usually reduced to a single unit performance curve approximated either through a piecewise linear curve [5], or by modeling the so-called local best efficiency points [6], the head dependence being therefore neglected. This dependence has been partially considered in only few mixed integer linear programming based models: in [7] the hydro plant generation characteristic is represented by three unit performance curves, each of which is approximated by a nonconcave piecewise linearization; in [8,9], an iterative procedure, formally known as successive mixed integer linear programming, is presented.…”

Section: Introductionmentioning

confidence: 99%

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Unit commitment and generation dispatch of a hydropower plant in a competitive electricity market

Pérez¹,

Wilhelmi²,

Arévalo³

2008

REPQJ

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Abstract. This paper presents a model to solve the short-term scheduling problem of a hydropower plant in a deregulated system, based on dynamic programming techniques. The objective of this model is to maximize the revenue obtained by selling energy in a competitive electricity market. The time horizon of the model is divided into hourly periods and ranges from one day to one week. The proposed model determines both the unit commitment and the power to be generated in each hour of the time horizon. The power is considered as a nonlinear function of the water discharge and the reservoir volume; the dependence of the units and plant operating limits on the available gross head has been taken into account; and the water discharged through the spillway has been also allowed for in the model. This approach has been applied to a practical case study, the results of which are analyzed in detail.

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Section: Plant Generation Characteristicmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Unit commitment and generation dispatch of a hydropower plant in a competitive electricity market

Pérez¹,

Wilhelmi²,

Arévalo³

2008

REPQJ

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show abstract

“…For an exhaustive overview we refer the reader to the recent survey [1]. In [2] the problem was formulated as a simple linear programming (LP) model by neglecting costs and constraints relevant to startups and shutdowns. In [3] a nonlinear programming (NLP) model with some simplified assumption was introduced.…”

Section: Introductionmentioning

confidence: 99%

An MILP Approach for Short-Term Hydro Scheduling and Unit Commitment With Head-Dependent Reservoir

Borghetti

d'Ambrosio

Lodi

et al. 2008

IEEE Trans. Power Syst.

281

128

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Abstract-The paper deals with a unit commitment problem of a generation company whose aim is to find the optimal scheduling of a multiunit pump-storage hydro power station, for a short term period in which the electricity prices are forecasted. The problem has a mixed-integer nonlinear structure, which makes very hard to handle the corresponding mathematical models. However, modern mixed-integer linear programming (MILP) software tools have reached a high efficiency, both in terms of solution accuracy and computing time. Hence we introduce MILP models of increasing complexity, which allow to accurately represent most of the hydroelectric system characteristics, and turn out to be computationally solvable. In particular we present a model that takes into account the head effects on power production through an enhanced linearization technique, and turns out to be more general and efficient than those available in the literature. The practical behavior of the models is analyzed through computational experiments on real-world data.

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“…For an exhaustive overview we refer the reader to the recent survey [103]. In [106] the problem was formulated as a simple Linear Programming (LP) model by neglecting costs and constraints relevant to start-ups and shutdowns. In [35] a Non-Linear Programming (NLP) model with some simplified assumption was introduced.…”

Section: Introductionmentioning

confidence: 99%

Application-oriented mixed integer non-linear programming

d'Ambrosio

2010

4OR-Q J Oper Res

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Optimal short-term scheduling for a large-scale cascaded hydro system

Cited by 45 publications

References 2 publications

Unit commitment and generation dispatch of a hydropower plant in a competitive electricity market

Unit commitment and generation dispatch of a hydropower plant in a competitive electricity market

An MILP Approach for Short-Term Hydro Scheduling and Unit Commitment With Head-Dependent Reservoir

Application-oriented mixed integer non-linear programming

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